Common Loon Predicted Habitat - CWHR B003 [ds2028]

CWHR Predicted Habitat Models represent areas of predicted suitable habitat for each species within its range. These models are built from the following principal inputs: 1) a statewide, best-available vegetation map (FVEG); 2) GIS data representing a species’ range; 3) the CWHR database of habitat suitability values for over 700 terrestrial vertebrate species. Habitat suitability ranks of Low (non-zero values less than 0.34), Medium (0.34-0.66), and High (greater than 0.66) are based on the maximum suitability value across the 3 species life requisites: reproduction, feeding, and cover. Note that previous versions of these Predicted Habitat Models used an average across the 3 life requisites in order to obtain an overall suitability score for each habitat type and stage class. Habitat suitability scores were developed based on habitat patch sizes greater than 40 acres in size and are best interpreted for habitat patches greater than 200 acres in size. The FVEG landcover dataset is an aggregation of multiple statewide landcover and regional vegetation mapping efforts, conducted at different points in time (approximately 1990 up to time of publishing) and at various resolutions, compiled by the California Department of Forestry and Fire Protection (CALFIRE). FVEG uses the most current and consistent data available for each region of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Crosswalks were used to attribute the various data sources according to the CWHR habitat-type classification system. Attributing FVEG with CWHR habitat types allows for the extraction of areas with non-zero suitability values for each species within the bounds of its range, creating a series of maps of predicted suitable habitat which are species-specific. Because FVEG is an amalgam of disparate landcover assessment efforts across the state, the predictive power for determining suitable habitat will vary between species, and possibly even regionally for species which are widely distributed. While these maps represent CDFW’s best estimate of the presence of suitable habitat for any given species in the CWHR system, these maps are also limited by several factors: 1) the accuracy and resolution of vegetation maps in a given region; 2) the dynamic nature of the landscape in which fire and other disturbance events alter conditions at a greater frequency than mapping efforts can track; 3) the currency of expert knowledge, particularly as species adapt to changing land and climate conditions and the shifting of other species’ ranges; 4) the frequency of species-specific surveys across a representative sample of a species’ entire range; 5) metapopulation dynamics, which describes the shifting of populations within their environment as result of numerous types of interactions and responses. CWHR GIS data representing predicted suitable habitat should not be used to indicate the presence or absence of a particular species at any specific site. CWHR predicted habitat models are named according to the 4-character alpha-numeric CWHR ID assigned to each species (5 characters in the case of subspecies or other sub-taxa). There is also a “CWHR Revision Tracking Table” containing a record for each species, its CWHR ID, scientific name, common name, and range and habitat model data revision history. CWHR species range models, predicted habitat models, and GIS data of the statewide distribution of all CWHR habitat types, along with the CWHR revision tracking table, are available for download at https://www.wildlife.ca.gov/Data/CWHR.CWHR预测栖息地模型指各物种在其分布范围内的潜在适宜栖息地区域。此类模型基于以下核心输入构建：1）全州最优可用植被图（FVEG）；2）表征物种分布范围的地理信息系统（Geographic Information System, GIS）数据；3）涵盖700余种陆生脊椎动物栖息地适宜性评分的CWHR数据库。 栖息地适宜性等级分为低（非零值小于0.34）、中（0.34~0.66）与高（大于0.66），其划分依据为物种三大生存必需条件——繁殖、觅食与隐蔽——的最大适宜性分值。需注意，早期版本的预测栖息地模型采用三大生存必需条件的平均分值，以生成各栖息地类型与演替阶段的综合适宜性评分。 栖息地适宜性评分基于面积大于40英亩的栖息地斑块制定，其最优解读场景为面积大于200英亩的栖息地斑块。 FVEG土地覆盖数据集由加州林业与消防局（CALFIRE, California Department of Forestry and Fire Protection）整合多项全州土地覆盖与区域植被制图项目成果而成，这些项目于不同时期（大致为1990年至发布时）以不同分辨率开展。FVEG采用加州各区域当前可得的最一致数据，并制定决策规则以处理重叠区域的图层优先级问题。同时通过属性匹配对照表（crosswalks），依据CWHR栖息地类型分类系统为各类数据源赋予对应属性。将FVEG与CWHR栖息地类型进行属性关联后，即可提取物种分布范围内具备非零适宜性分值的区域，进而生成一系列物种专属的适宜栖息地预测分布图。 由于FVEG整合了全州范围内各类不同来源的土地覆盖评估成果，其判定适宜栖息地的预测能力会因物种而异，对于分布广泛的物种甚至可能存在区域差异。尽管这些地图代表了加州鱼类与野生动物部（CDFW, California Department of Fish and Wildlife）针对CWHR系统内任意物种的适宜栖息地存在情况所做出的最优估算，但此类地图仍受多项因素限制：1）特定区域植被图的精度与分辨率；2）景观的动态特性——火灾与其他干扰事件改变栖息地条件的频率高于制图更新的频率；3）专家知识的时效性，尤其是在物种适应土地与气候条件变化、其他物种分布范围发生迁移的背景下；4）针对物种完整分布范围的代表性样本开展物种专属调查的频率；5）集合种群动态——即种群在多种交互作用与环境响应下发生的空间移位。 CWHR预测栖息地的GIS数据不得用于判定特定物种在某一具体点位的存在与否。CWHR预测栖息地模型以各物种对应的4位字母数字组合CWHR ID命名（亚种或其他下级类群的物种则使用5位ID）。此外还设有“CWHR修订追踪表”，其中包含各物种的CWHR ID、学名、俗名、分布范围以及栖息地模型数据的修订历史记录。 CWHR物种分布模型、预测栖息地模型、全加州CWHR栖息地类型全域分布GIS数据，以及CWHR修订追踪表，均可在https://www.wildlife.ca.gov/Data/CWHR 网站下载获取。